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Add conditional compile for gru opt #17368

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Merged
zhaoyuchen2018 merged 6 commits into from
May 16, 2019
Merged

Add conditional compile for gru opt #17368

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3c83e5b
improve gru unit performance.
zhaoyuchen2018 Mar 21, 2019
53a35e6
Merge commit 'refs/pull/16338/head' of https://github.com/PaddlePaddl…
zhaoyuchen2018 May 8, 2019
4915ccd
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zhaoyuchen2018 May 9, 2019
8da9c70
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zhaoyuchen2018 May 13, 2019
c6aea85
Add conditional compile for gru opt
zhaoyuchen2018 May 13, 2019
fef11df
refine code.
zhaoyuchen2018 May 14, 2019
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44 changes: 25 additions & 19 deletions paddle/fluid/operators/math/gru_compute.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -30,25 +30,31 @@ struct GRUUnitFunctor<platform::CUDADeviceContext, T> {
dim3 threads;
dim3 grid;
if (batch_size == 1) {
constexpr int tiled_size = 16;
int frame_blocks = (frame_size * 2 + tiled_size - 1) / tiled_size;
threads = dim3(tiled_size, 1);
grid = dim3(frame_blocks, 1);

detail::KeFastCollectiveGruGate<T,
tiled_size><<<grid, threads, 0, stream>>>(
value.gate_value, value.prev_out_value, value.gate_weight,
value.reset_output_value, frame_size, active_gate);

frame_blocks = (frame_size + tiled_size - 1) / tiled_size;
grid = dim3(frame_blocks, 1);
detail::KeFastCollectiveGruOut<T,
tiled_size><<<grid, threads, 0, stream>>>(
value.state_weight, value.prev_out_value, value.output_value,
value.gate_value, value.reset_output_value, frame_size, active_node,
origin_mode);

return;
if (context.GetComputeCapability() >= 70) {
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@tensor-tang tensor-tang May 16, 2019

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please do not use magic number 70, you can address in next PR.

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@zhaoyuchen2018 zhaoyuchen2018 May 16, 2019

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sure

constexpr int tiled_size = 16;
int frame_blocks = (frame_size * 2 + tiled_size - 1) / tiled_size;
threads = dim3(tiled_size, 1);
grid = dim3(frame_blocks, 1);
detail::KeFastCollectiveGruGate<
T, tiled_size><<<grid, threads, 0, stream>>>(
value.gate_value, value.prev_out_value, value.gate_weight,
value.reset_output_value, frame_size, active_gate);

frame_blocks = (frame_size + tiled_size - 1) / tiled_size;
grid = dim3(frame_blocks, 1);
detail::KeFastCollectiveGruOut<
T, tiled_size><<<grid, threads, 0, stream>>>(
value.state_weight, value.prev_out_value, value.output_value,
value.gate_value, value.reset_output_value, frame_size, active_node,
origin_mode);

return;
} else {
int frame_per_block = frame_size <= 1024 ? frame_size : 1024;
int frame_blocks = (frame_size + 1024 - 1) / 1024;
threads = dim3(frame_per_block, 1);
grid = dim3(frame_blocks, 1);
}
} else {
threads = dim3(32, 32);
grid = dim3((frame_size + 32 - 1) / 32, (batch_size + 32 - 1) / 32);
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